{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import torch\n",
    "import torch.nn as nn\n",
    "import torchvision\n",
    "import torchvision.transforms as transforms\n",
    "import matplotlib.pyplot as plt\n",
    "from VGG_hc import VGG19\n",
    "import time\n",
    "import os\n",
    "os.environ['CUDA_VISIBLE_DEVICES'] = '0,1'\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Processing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 利用torchvision对图像数据预处理\n",
    "train_transform = transforms.Compose([\n",
    "    transforms.Resize(256),\n",
    "    transforms.RandomResizedCrop(224),\n",
    "    transforms.RandomAffine(degrees=15,scale=(0.8,1.5)),\n",
    "    transforms.ToTensor(),\n",
    "    transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])\n",
    "])\n",
    "\n",
    "val_transform = transforms.Compose([\n",
    "    transforms.Resize(256),\n",
    "    transforms.CenterCrop(224),\n",
    "    transforms.ToTensor(),\n",
    "    transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])\n",
    "])\n",
    "\n",
    "trainset = torchvision.datasets.ImageFolder(root='../data/train/', transform=train_transform)\n",
    "trainloader = torch.utils.data.DataLoader(trainset, batch_size=128, shuffle=True, num_workers=4)\n",
    "\n",
    "valset = torchvision.datasets.ImageFolder(root='../data/val/', transform=val_transform)\n",
    "valloader = torch.utils.data.DataLoader(valset, batch_size=128, shuffle=False, num_workers=4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "165\n",
      "32\n"
     ]
    }
   ],
   "source": [
    "# 展示训练样本和测试样本数\n",
    "print(len(trainloader))\n",
    "print(len(valloader))\n",
    "# CPU 或者 GPU\n",
    "device = torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')\n",
    "# 初始化网络,加载预训练模型\n",
    "model = VGG19(num_classes=2, init_weights=False)\n",
    "model_dict = model.state_dict()\n",
    "state_dict = torch.load('pretrained/vgg19-dcbb9e9d.pth')\n",
    "new_state_dict = {k: v for k, v in state_dict.items() if k in model_dict}\n",
    "model_dict.update(new_state_dict)\n",
    "model.load_state_dict(model_dict)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Training"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "We are using 2 GPUs!\n",
      "epoch 0,iter 20,train accuracy: 63.5547%   loss:  0.6335\n",
      "epoch 0,iter 40,train accuracy: 83.4766%   loss:  0.4123\n",
      "epoch 0,iter 60,train accuracy: 86.4453%   loss:  0.3179\n",
      "epoch 0,iter 80,train accuracy: 86.3672%   loss:  0.2857\n",
      "epoch 0,iter 100,train accuracy: 89.7656%   loss:  0.2436\n",
      "epoch 0,iter 120,train accuracy: 89.6094%   loss:  0.2351\n",
      "epoch 0,iter 140,train accuracy: 91.0938%   loss:  0.1999\n",
      "epoch 0,iter 160,train accuracy: 90.3125%   loss:  0.2011\n",
      "waitting for Val...\n",
      "epoch 0  The ValSet accuracy is 98.3000% \n",
      "\n",
      "Find Better Model and Saving it...\n",
      "Saved!\n",
      "Training complete in 3m 5s\n",
      "Now the best val Acc is 98.3000%\n",
      "epoch 1,iter 20,train accuracy: 91.1328%   loss:  0.1857\n",
      "epoch 1,iter 40,train accuracy: 91.9922%   loss:  0.1810\n",
      "epoch 1,iter 60,train accuracy: 91.7188%   loss:  0.1898\n",
      "epoch 1,iter 80,train accuracy: 90.8203%   loss:  0.1916\n",
      "epoch 1,iter 100,train accuracy: 92.6172%   loss:  0.1683\n",
      "epoch 1,iter 120,train accuracy: 91.9922%   loss:  0.1691\n",
      "epoch 1,iter 140,train accuracy: 91.6406%   loss:  0.1804\n",
      "epoch 1,iter 160,train accuracy: 92.8125%   loss:  0.1651\n",
      "waitting for Val...\n",
      "epoch 1  The ValSet accuracy is 98.3250% \n",
      "\n",
      "Find Better Model and Saving it...\n",
      "Saved!\n",
      "Training complete in 6m 14s\n",
      "Now the best val Acc is 98.3250%\n",
      "epoch 2,iter 20,train accuracy: 93.8672%   loss:  0.1528\n",
      "epoch 2,iter 40,train accuracy: 92.2656%   loss:  0.1624\n",
      "epoch 2,iter 60,train accuracy: 92.5000%   loss:  0.1712\n",
      "epoch 2,iter 80,train accuracy: 93.4375%   loss:  0.1549\n",
      "epoch 2,iter 100,train accuracy: 91.7578%   loss:  0.1817\n",
      "epoch 2,iter 120,train accuracy: 93.1641%   loss:  0.1592\n",
      "epoch 2,iter 140,train accuracy: 92.7344%   loss:  0.1649\n",
      "epoch 2,iter 160,train accuracy: 92.4609%   loss:  0.1574\n",
      "waitting for Val...\n",
      "epoch 2  The ValSet accuracy is 98.5750% \n",
      "\n",
      "Find Better Model and Saving it...\n",
      "Saved!\n",
      "Training complete in 9m 23s\n",
      "Now the best val Acc is 98.5750%\n",
      "epoch 3,iter 20,train accuracy: 92.4219%   loss:  0.1653\n",
      "epoch 3,iter 40,train accuracy: 93.0859%   loss:  0.1604\n",
      "epoch 3,iter 60,train accuracy: 92.8125%   loss:  0.1509\n",
      "epoch 3,iter 80,train accuracy: 93.6719%   loss:  0.1473\n",
      "epoch 3,iter 100,train accuracy: 93.0469%   loss:  0.1561\n",
      "epoch 3,iter 120,train accuracy: 92.6562%   loss:  0.1639\n",
      "epoch 3,iter 140,train accuracy: 93.7109%   loss:  0.1355\n",
      "epoch 3,iter 160,train accuracy: 93.1641%   loss:  0.1429\n",
      "waitting for Val...\n",
      "epoch 3  The ValSet accuracy is 98.6000% \n",
      "\n",
      "Find Better Model and Saving it...\n",
      "Saved!\n",
      "Training complete in 12m 34s\n",
      "Now the best val Acc is 98.6000%\n",
      "epoch 4,iter 20,train accuracy: 93.0078%   loss:  0.1616\n",
      "epoch 4,iter 40,train accuracy: 93.4766%   loss:  0.1432\n",
      "epoch 4,iter 60,train accuracy: 93.1641%   loss:  0.1524\n",
      "epoch 4,iter 80,train accuracy: 92.5391%   loss:  0.1571\n",
      "epoch 4,iter 100,train accuracy: 92.5000%   loss:  0.1565\n",
      "epoch 4,iter 120,train accuracy: 93.2422%   loss:  0.1648\n",
      "epoch 4,iter 140,train accuracy: 93.7500%   loss:  0.1446\n",
      "epoch 4,iter 160,train accuracy: 93.9844%   loss:  0.1369\n",
      "waitting for Val...\n",
      "epoch 4  The ValSet accuracy is 98.5750% \n",
      "\n",
      "Training complete in 15m 39s\n",
      "Now the best val Acc is 98.6000%\n",
      "epoch 5,iter 20,train accuracy: 93.8281%   loss:  0.1392\n",
      "epoch 5,iter 40,train accuracy: 93.3203%   loss:  0.1502\n",
      "epoch 5,iter 60,train accuracy: 93.5938%   loss:  0.1467\n",
      "epoch 5,iter 80,train accuracy: 94.4922%   loss:  0.1380\n",
      "epoch 5,iter 100,train accuracy: 94.0234%   loss:  0.1369\n",
      "epoch 5,iter 120,train accuracy: 93.7891%   loss:  0.1497\n",
      "epoch 5,iter 140,train accuracy: 93.0469%   loss:  0.1479\n",
      "epoch 5,iter 160,train accuracy: 92.5781%   loss:  0.1644\n",
      "waitting for Val...\n",
      "epoch 5  The ValSet accuracy is 98.6000% \n",
      "\n",
      "Training complete in 18m 43s\n",
      "Now the best val Acc is 98.6000%\n",
      "epoch 6,iter 20,train accuracy: 93.4766%   loss:  0.1406\n",
      "epoch 6,iter 40,train accuracy: 92.8906%   loss:  0.1510\n",
      "epoch 6,iter 60,train accuracy: 93.3203%   loss:  0.1550\n",
      "epoch 6,iter 80,train accuracy: 93.5156%   loss:  0.1424\n",
      "epoch 6,iter 100,train accuracy: 93.6719%   loss:  0.1456\n",
      "epoch 6,iter 120,train accuracy: 93.8672%   loss:  0.1346\n",
      "epoch 6,iter 140,train accuracy: 93.8281%   loss:  0.1445\n",
      "epoch 6,iter 160,train accuracy: 94.0234%   loss:  0.1399\n",
      "waitting for Val...\n",
      "epoch 6  The ValSet accuracy is 98.7000% \n",
      "\n",
      "Find Better Model and Saving it...\n",
      "Saved!\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/huangchao/anaconda3/envs/Funny/lib/python3.6/site-packages/ipykernel_launcher.py:91: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training complete in 21m 53s\n",
      "Now the best val Acc is 98.7000%\n",
      "epoch 7,iter 20,train accuracy: 92.6953%   loss:  0.1612\n",
      "epoch 7,iter 40,train accuracy: 93.5938%   loss:  0.1377\n",
      "epoch 7,iter 60,train accuracy: 94.1016%   loss:  0.1337\n",
      "epoch 7,iter 80,train accuracy: 93.6328%   loss:  0.1413\n",
      "epoch 7,iter 100,train accuracy: 94.1406%   loss:  0.1212\n",
      "epoch 7,iter 120,train accuracy: 93.8672%   loss:  0.1365\n",
      "epoch 7,iter 140,train accuracy: 93.0859%   loss:  0.1451\n",
      "epoch 7,iter 160,train accuracy: 93.9062%   loss:  0.1360\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/huangchao/anaconda3/envs/Funny/lib/python3.6/site-packages/ipykernel_launcher.py:48: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).\n",
      "/home/huangchao/anaconda3/envs/Funny/lib/python3.6/site-packages/ipykernel_launcher.py:57: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "waitting for Val...\n",
      "epoch 7  The ValSet accuracy is 98.7000% \n",
      "\n",
      "Training complete in 24m 57s\n",
      "Now the best val Acc is 98.7000%\n",
      "epoch 8,iter 20,train accuracy: 93.5156%   loss:  0.1388\n",
      "epoch 8,iter 40,train accuracy: 94.3359%   loss:  0.1349\n",
      "epoch 8,iter 60,train accuracy: 94.1406%   loss:  0.1331\n",
      "epoch 8,iter 80,train accuracy: 95.0000%   loss:  0.1358\n",
      "epoch 8,iter 100,train accuracy: 94.3750%   loss:  0.1278\n",
      "epoch 8,iter 120,train accuracy: 94.3359%   loss:  0.1272\n",
      "epoch 8,iter 140,train accuracy: 93.6328%   loss:  0.1414\n",
      "epoch 8,iter 160,train accuracy: 93.2031%   loss:  0.1559\n",
      "waitting for Val...\n",
      "epoch 8  The ValSet accuracy is 98.7000% \n",
      "\n",
      "Training complete in 28m 1s\n",
      "Now the best val Acc is 98.7000%\n",
      "epoch 9,iter 20,train accuracy: 94.8828%   loss:  0.1180\n",
      "epoch 9,iter 40,train accuracy: 94.1016%   loss:  0.1394\n",
      "epoch 9,iter 60,train accuracy: 93.1641%   loss:  0.1476\n",
      "epoch 9,iter 80,train accuracy: 93.6719%   loss:  0.1306\n",
      "epoch 9,iter 100,train accuracy: 93.4766%   loss:  0.1380\n",
      "epoch 9,iter 120,train accuracy: 94.4922%   loss:  0.1285\n",
      "epoch 9,iter 140,train accuracy: 94.2969%   loss:  0.1296\n",
      "epoch 9,iter 160,train accuracy: 93.9844%   loss:  0.1434\n",
      "waitting for Val...\n",
      "epoch 9  The ValSet accuracy is 98.7500% \n",
      "\n",
      "Find Better Model and Saving it...\n",
      "Saved!\n",
      "Training complete in 31m 9s\n",
      "Now the best val Acc is 98.7500%\n"
     ]
    },
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\n",
      "text/plain": [
       "<Figure size 792x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 792x576 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 792x576 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 792x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 792x576 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 792x576 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 792x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 792x576 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 792x576 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 792x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 792x576 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 792x576 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 792x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 792x576 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 792x576 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 792x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 792x576 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 792x576 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 792x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 792x576 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 792x576 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 792x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 792x576 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 792x576 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 792x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 792x576 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 792x576 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 792x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 查看GPU可用情况\n",
    "if torch.cuda.device_count()>1:\n",
    "    print('We are using',torch.cuda.device_count(),'GPUs!')\n",
    "    model = nn.DataParallel(model)\n",
    "model.to(device)\n",
    "\n",
    "# 定义loss function和优化器\n",
    "criterion = nn.CrossEntropyLoss()\n",
    "optimizer = torch.optim.SGD(model.parameters(), lr=0.0001, momentum=0.9)\n",
    "\n",
    "# 保存每个epoch后的Accuracy Loss Val_Accuracy\n",
    "Accuracy = []\n",
    "Loss = []\n",
    "Val_Accuracy = []\n",
    "BEST_VAL_ACC = 0.\n",
    "# 训练\n",
    "since = time.time()\n",
    "for epoch in range(10):\n",
    "    train_loss = 0.\n",
    "    train_accuracy = 0.\n",
    "    run_accuracy = 0.\n",
    "    run_loss =0.\n",
    "    total = 0.\n",
    "    model.train()\n",
    "    for i,data in enumerate(trainloader,0):\n",
    "        images, labels = data\n",
    "        images = images.to(device)\n",
    "        labels = labels.to(device)  \n",
    "        # 经典四步\n",
    "        optimizer.zero_grad()\n",
    "        outs = model(images)\n",
    "        loss = criterion(outs, labels)\n",
    "        loss.backward()\n",
    "        optimizer.step()\n",
    "        # 输出状态\n",
    "        total += labels.size(0)\n",
    "        run_loss += loss.item()\n",
    "        _,prediction = torch.max(outs,1)\n",
    "        run_accuracy += (prediction == labels).sum().item()\n",
    "        if i % 20 == 19:\n",
    "            print('epoch {},iter {},train accuracy: {:.4f}%   loss:  {:.4f}'.format(epoch, i+1, 100*run_accuracy/(labels.size(0)*20), run_loss/20))\n",
    "            train_accuracy += run_accuracy\n",
    "            train_loss += run_loss\n",
    "            run_accuracy, run_loss = 0., 0.\n",
    "    Loss.append(train_loss/total)\n",
    "    Accuracy.append(100*train_accuracy/total)\n",
    "    # 可视化训练过程\n",
    "    fig1, ax1 = plt.subplots(figsize=(11, 8))\n",
    "    ax1.plot(range(0, epoch+1, 1), Accuracy)\n",
    "    ax1.set_title(\"Average trainset accuracy vs epochs\")\n",
    "    ax1.set_xlabel(\"Epoch\")\n",
    "    ax1.set_ylabel(\"Avg. train. accuracy\")\n",
    "    plt.savefig('Train_accuracy_vs_epochs.png')\n",
    "    plt.clf()\n",
    "    plt.close()\n",
    "    \n",
    "    fig2, ax2 = plt.subplots(figsize=(11, 8))\n",
    "    ax2.plot(range(epoch+1), Loss)\n",
    "    ax2.set_title(\"Average trainset loss vs epochs\")\n",
    "    ax2.set_xlabel(\"Epoch\")\n",
    "    ax2.set_ylabel(\"Current loss\")\n",
    "    plt.savefig('loss_vs_epochs.png')\n",
    "\n",
    "    plt.clf()\n",
    "    plt.close()\n",
    "    # 验证\n",
    "    acc = 0.\n",
    "    model.eval()\n",
    "    print('waitting for Val...')\n",
    "    with torch.no_grad():\n",
    "        accuracy = 0.\n",
    "        total =0\n",
    "        for data in valloader:\n",
    "            images, labels = data\n",
    "            images = images.to(device)\n",
    "            labels = labels.to(device)\n",
    "            out = model(images)\n",
    "            _, prediction = torch.max(out, 1)\n",
    "            total += labels.size(0)\n",
    "            accuracy += (prediction == labels).sum().item()\n",
    "            acc = 100.*accuracy/total\n",
    "    print('epoch {}  The ValSet accuracy is {:.4f}% \\n'.format(epoch, acc))\n",
    "    Val_Accuracy.append(acc)\n",
    "    if acc > BEST_VAL_ACC:\n",
    "        print('Find Better Model and Saving it...')\n",
    "        if not os.path.isdir('checkpoint'):\n",
    "            os.mkdir('checkpoint')\n",
    "        torch.save(model.state_dict(), './checkpoint/VGG19_Cats_Dogs_hc.pth')\n",
    "        BEST_VAL_ACC = acc\n",
    "        print('Saved!')\n",
    "    \n",
    "    fig3, ax3 = plt.subplots(figsize=(11, 8))\n",
    "\n",
    "    ax3.plot(range(epoch+1),Val_Accuracy )\n",
    "    ax3.set_title(\"Average Val accuracy vs epochs\")\n",
    "    ax3.set_xlabel(\"Epoch\")\n",
    "    ax3.set_ylabel(\"Current Val accuracy\")\n",
    "\n",
    "    plt.savefig('val_accuracy_vs_epoch.png')\n",
    "    plt.close()\n",
    "    time_elapsed = time.time() - since\n",
    "    print('Training complete in {:.0f}m {:.0f}s'.format(time_elapsed // 60, time_elapsed%60))\n",
    "    print('Now the best val Acc is {:.4f}%'.format(BEST_VAL_ACC))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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